MYD14 v006

MODIS/Aqua Thermal Anomalies/Fire 5-Minute L2 Swath 1 km


PI: Louis Giglio

The MYD14 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MYD14 Version 6.1 data product.

Description

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire MYD14 Version 6 product is produced daily in 5-minute temporal satellite increments (swaths). The MYD14 product is used to generate all of the higher level fire products, but can also be used to identify fires and other thermal anomalies, such as volcanoes. Each swath of data is approximately 2,030 kilometers along track (long), and 2,300 kilometers across track (wide).

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Characteristics

Improvements/Changes from Previous Versions

  • Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.
  • Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests.
  • Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.
  • Detects small fires using dynamic thresholding.
  • Processes ocean and coastline pixels to detect fire from oil rigs.
  • The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels.”

Product Maturity

Validation at stage 3 has been achieved for all MODIS Thermal Anomalies and Fire products. Further details regarding MODIS land product validation for the MYD14 data product is available from the MODIS land team validation site.

Collection and Granule

Collection

Characteristic Description
CollectionAqua MODIS
DOI10.5067/MODIS/MYD14.006
File Size0.25 MB
Temporal Resolution< Daily
Temporal Extent2002-07-04 to 2023-02-25
Spatial ExtentGlobal
Coordinate SystemNone (Swath)
DatumN/A
File FormatHDF-EOS
Geographic Dimensions2300 km x 2030

Granule

Characteristic Description
Number of Science Dataset (SDS) Layers30
Columns/Rows1354 x 2030
Pixel Size1000 m

Layers / Variables

SDS Name Description Units Data Type Fill Value No Data Value Valid Range Scale Factor
Fire Mask Confidence of fire Class Flag 8-bit unsigned integer 0 N/A 1 to 9 N/A
Algorithm QA Pixel quality indicators Bit Field 32-bit unsigned integer 4.3E+09 N/A 0 to 4294966531 N/A
FP_line Granule line of fire pixel N/A 16-bit signed integer N/A N/A N/A N/A
FP_sample Granule sample of fire pixel N/A 16-bit signed integer N/A N/A N/A N/A
FP_latitude Latitude at center of fire pixel Degree 32-bit floating point N/A N/A -90 to 90 N/A
FP_longitude Longitude at center of fire pixel Degree 32-bit floating point N/A N/A -180 to 180 N/A
FP_R2 Near-IR (band 2) reflectance of fire pixel (daytime only) N/A 32-bit floating point N/A N/A N/A N/A
FP_T21 Channel 21/22 brightness temperature of fire pixel Kelvin 32-bit floating point N/A N/A N/A N/A
FP_T31 Channel 31 brightness temperature of fire pixel Kelvin 32-bit floating point N/A N/A N/A N/A
FP_MeanT21 Background channel 21/22 brightness temperature Kelvin 32-bit floating point N/A N/A N/A N/A
FP_MeanT31 Background channel 31 brightness temperature Kelvin 32-bit floating point N/A N/A N/A N/A
FP_MeanDT Background brightness temperature difference Kelvin 32-bit floating point N/A N/A N/A N/A
FP_MAD_T21 Background channel 21/22 brightness temperature mean absolute deviation Kelvin 32-bit floating point N/A N/A N/A N/A
FP_MAD_T31 Background channel 31 brightness temperature mean absolute deviation Kelvin 64-bit floating point N/A N/A N/A N/A
FP_MAD_DT Background  brightness temperature difference mean absolute deviation Kelvin 64-bit floating point N/A N/A N/A N/A
FP_power Fire radiative power Megawatts 64-bit floating point N/A N/A N/A N/A
FP_AdjCloud Number of adjacent cloud pixels N/A 8-bit unsigned integer N/A N/A 0 to 8 N/A
FP_AdjWater Number of adjacent water pixels N/A 8-bit unsigned integer N/A N/A 0 to 8 N/A
FP_WinSize Background window size N/A 8-bit unsigned integer N/A N/A N/A N/A
FP_NumValid Number of valid background pixels N/A 16-bit signed integer N/A N/A N/A N/A
FP_confidence Detection confidence estimate Percent 8-bit unsigned integer N/A N/A 1 to 100 N/A
FP_land Land flag (0 = water pixel; 1 = land pixel) N/A 8-bit unsigned integer N/A N/A N/A N/A
FP_MeanR2 Background channel 2 reflectance N/A 32-bit floating point N/A N/A N/A N/A
FP_MAD_R2 Background channel 2 reflectance mean absolute deviation N/A 32-bit floating point N/A N/A N/A N/A
FP_ViewZenAng View zenith angle Degree 32-bit floating point N/A N/A N/A N/A
FP_SolZenAng Solar zenith angle Degree 32-bit floating point N/A N/A 0 to 180 N/A
FP_RelAzAng Relative azimuth angle Degree 32-bit floating point N/A N/A -180 to 180 N/A
FP_CMG_row CMG row N/A 16-bit signed integer N/A N/A N/A N/A
FP_CMG_col CMG column N/A 16-bit signed integer N/A N/A N/A N/A
CMG_night¹ Night flag N/A 16-bit unsigned integer N/A N/A N/A N/A

¹Additional Climate Modeling Grid (CMG) layers are also found among the SDSs. Those CMG layers contain information used for the generation of Level 4 CMG products.

MYD14 fire mask pixel classes

Value Description
0 Not processed (missing input data)
1 Not processed (obsolete; not used since Collection 1)
2 Not processed (other reason)
3 Non-fire water pixel
4 Cloud (land or water)
5 Non-fire land pixel
6 Unknown (land or water)
7 Fire (low confidence, land or water)
8 Fire (nominal confidence, land or water)
9 Fire (high confidence, land or water)

Product Quality

The quality layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the quality layer.

The Quality Assessment (QA) bit flags for the quality layer are provided in Table 6 of the User Guide.

Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.

Known Issues

Known issues are described on the MODIS Land Quality Assessment website and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.


About the image

Aqua MODIS fire data from the MYD14 product over western United States, September 15, 2018.

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Documentation

User Guide
Algorithm Theoretical Basis Document (ATBD)
File Specification

Using the Data

Access Data

Citation

DOI: 10.5067/MODIS/MYD14.006